Cascading dynamics and mitigation assessment in power system disturbances via a hidden failure model

A hidden failure embedded DC model of power transmission systems has been developed to study the power law distributions observed in North American blackout data. We investigate the impacts of several model parameters on the global dynamics and evaluate possible mitigation measures. The main parameters include system loading level, hidden failure probability, spinning reserve capacity and control strategy. The sensitivity of power-law behavior with respect to each of these four parameters and the corresponding blackout mitigation are discussed and illustrated via simulation results from the WSCC 179-bus equivalent system and the IEEE 118-bus test system. It is our intention that this study can provide guidance on when and how the suggested mitigation methods might be effective.

[1]  Ia An N Do.  A LOADING-DEPENDENT MODEL OF PROBABILISTIC CASCADING FAILURE , 2005 .

[2]  James S. Thorp,et al.  Anatomy of power system disturbances : importance sampling , 1998 .

[3]  James S. Thorp,et al.  A stochastic study of hidden failures in power system protection , 1999, Decis. Support Syst..

[4]  Ian Dobson,et al.  Examining criticality of blackouts in power system models with cascading events , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[5]  I. Dobson,et al.  A LOADING-DEPENDENT MODEL OF PROBABILISTIC CASCADING FAILURE , 2005, Probability in the Engineering and Informational Sciences.

[6]  B A Carreras,et al.  Complex dynamics of blackouts in power transmission systems. , 2004, Chaos.

[7]  Ian Dobson,et al.  A probabilistic loading-dependent model of cascading failure and possible implications for blackouts , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[8]  G. Parmigiani.  Large Deviation Techniques in Decision, Simulation and Estimation , 1992 .

[9]  V. E. Lynch,et al.  Critical points and transitions in an electric power transmission model for cascading failure blackouts. , 2002, Chaos.

[10]  Ian Dobson,et al.  Evidence for self-organized criticality in a time series of electric power system blackouts , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.

[11]  Ian Dobson,et al.  Evidence for self-organized criticality in electric power system blackouts , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[12]  James S. Thorp,et al.  Analysis of electric power system disturbance data , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[13]  Ian Dobson,et al.  Blackout mitigation assessment in power transmission systems , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[14]  Ian Dobson,et al.  Modeling blackout dynamics in power transmission networks with simple structure , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[15]  James S. Thorp,et al.  Enhancing reliability of power protection systems economically in the post-restructuring era , 2000 .

[16]  Ian Dobson,et al.  Initial evidence for self-organized criticality in electric power system blackouts , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[17]  Ian Dobson,et al.  Dynamics, criticality and self-organization in a model for blackouts in power transmission systems , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[18]  Ian Dobson,et al.  An initial model fo complex dynamics in electric power system blackouts , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.